Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	132,948
2	South Dakota	129,955
3	Rhode Island	124,777
4	Utah	118,460
5	Arizona	114,625
6	Tennessee	114,449
7	Oklahoma	109,557
8	Iowa	109,115
9	Arkansas	108,615
10	Wisconsin	107,732
11	Nebraska	106,438
12	South Carolina	104,123
13	Alabama	103,907
14	Kansas	103,580
15	Mississippi	101,339
16	Indiana	100,665
17	Idaho	98,815
18	Nevada	97,459
19	Illinois	96,060
20	Montana	95,999
21	Wyoming	95,806
22	New Jersey	95,570
23	Georgia	95,441
24	Texas	94,591
25	Louisiana	94,433
26	Kentucky	94,407
27	Missouri	93,909
28	Delaware	93,578
29	Florida	92,608
30	California	91,901
31	New York	90,576
32	New Mexico	90,091
33	Minnesota	88,663
34	Massachusetts	87,976
35	North Carolina	85,263
36	Ohio	85,009
37	Alaska	82,634
38	Connecticut	82,553
39	Colorado	77,767
40	Pennsylvania	76,477
41	West Virginia	76,073
42	Virginia	70,115
43	Michigan	68,116
44	Maryland	65,471
45	District of Columbia	60,660
46	New Hampshire	58,370
47	Washington	46,589
48	Puerto Rico	42,885
49	Oregon	38,017
50	Maine	35,404
51	Vermont	27,413
52	Hawaii	20,074

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Rhode Island	529
2	New Jersey	407
3	Alabama	394
4	Connecticut	350
5	Michigan	349
6	New York	349
7	Alaska	298
8	Tennessee	284
9	Delaware	253
10	Idaho	239
11	Montana	239
12	Pennsylvania	212
13	North Carolina	211
14	Massachusetts	196
15	Florida	189
16	New Hampshire	184
17	South Carolina	173
18	Texas	173
19	Kentucky	164
20	Wyoming	164
21	West Virginia	161
22	Minnesota	151
23	Georgia	150
24	Iowa	145
25	Nebraska	145
26	Utah	145
27	Virginia	145
28	District of Columbia	141
29	Maine	140
30	North Dakota	134
31	South Dakota	129
32	Ohio	128
33	Kansas	121
34	Maryland	120
35	Louisiana	115
36	Vermont	115
37	Illinois	114
38	Washington	111
39	Colorado	109
40	Wisconsin	97
41	New Mexico	94
42	Indiana	93
43	Nevada	93
44	Arkansas	92
45	Mississippi	92
46	Oklahoma	87
47	Missouri	85
48	Arizona	72
49	California	70
50	Oregon	57
51	Hawaii	36
52	Puerto Rico	36

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,702
2	New York	2,502
3	Rhode Island	2,442
4	Massachusetts	2,427
5	Mississippi	2,330
6	Arizona	2,278
7	Connecticut	2,189
8	South Dakota	2,164
9	Louisiana	2,141
10	Alabama	2,113
11	North Dakota	1,955
12	Pennsylvania	1,933
13	Indiana	1,915
14	New Mexico	1,847
15	Illinois	1,835
16	Arkansas	1,824
17	Iowa	1,796
18	South Carolina	1,734
19	Tennessee	1,692
20	Michigan	1,682
21	Georgia	1,676
22	Nevada	1,671
23	Kansas	1,660
24	Texas	1,620
25	Delaware	1,556
26	Ohio	1,539
27	Florida	1,513
28	District of Columbia	1,479
29	California	1,441
30	Missouri	1,434
31	West Virginia	1,431
32	Maryland	1,339
33	Montana	1,308
34	Wisconsin	1,237
35	Minnesota	1,210
36	Oklahoma	1,210
37	Wyoming	1,197
38	Virginia	1,189
39	Kentucky	1,163
40	Nebraska	1,156
41	North Carolina	1,123
42	Idaho	1,083
43	Colorado	1,065
44	New Hampshire	884
45	Washington	684
46	Puerto Rico	652
47	Utah	635
48	Oregon	559
49	Maine	539
50	Alaska	400
51	Vermont	347
52	Hawaii	316

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Oklahoma	7
2	Rhode Island	6
3	West Virginia	6
4	Kentucky	5
5	Louisiana	5
6	Virginia	5
7	Georgia	4
8	Idaho	4
9	Massachusetts	4
10	Pennsylvania	4
11	Texas	4
12	Arkansas	3
13	California	3
14	Connecticut	3
15	Delaware	3
16	Florida	3
17	Mississippi	3
18	Nevada	3
19	New Jersey	3
20	New Mexico	3
21	New York	3
22	Ohio	3
23	South Carolina	3
24	Alabama	2
25	Iowa	2
26	Maryland	2
27	North Carolina	2
28	Oregon	2
29	Arizona	1
30	Colorado	1
31	District of Columbia	1
32	Illinois	1
33	Indiana	1
34	Kansas	1
35	Michigan	1
36	Missouri	1
37	Montana	1
38	South Dakota	1
39	Utah	1
40	Vermont	1
41	Washington	1
42	Wisconsin	1
43	Wyoming	1
44	Alaska	0
45	Hawaii	0
46	Maine	0
47	Minnesota	0
48	Nebraska	0
49	New Hampshire	0
50	North Dakota	0
51	Puerto Rico	0
52	Tennessee	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Crowley	Colorado	346,972	1	99
Chattahoochee	Georgia	303,567	2	99
Bent	Colorado	265,914	3	99
Lincoln	Arkansas	243,474	4	99
Dewey	South Dakota	243,381	5	99
Davidson	Tennessee	132,915	220	92
Richland	South Carolina	102,853	1057	66
York	South Carolina	98,744	1250	60
Orange	California	83,200	1979	37
Pierce	Washington	44,626	2905	7

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Gove	Kansas	8,346	1	99
Jerauld	South Dakota	7,948	2	99
Foard	Texas	7,792	3	99
Galax city	Virginia	7,720	4	99
Emporia city	Virginia	7,669	5	99
Orange	California	1,420	1811	42
Davidson	Tennessee	1,259	2003	36
Richland	South Carolina	1,251	2023	35
York	South Carolina	1,224	2060	34
Pierce	Washington	652	2710	13

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.